Computational Intelligence - (Texts in Computer Science) 2nd Edition (Hardcover)
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<p/><br></br><p><b> Book Synopsis </b></p></br></br>This textbook provides a clear and logical introduction to the field, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. This enhanced second edition has been fully revised and expanded with new content on swarm intelligence, deep learning, fuzzy data analysis, and discrete decision graphs. <br>Features: provides supplementary material at an associated website; contains numerous classroom-tested examples and definitions throughout the text; presents useful insights into all that is necessary for the successful application of computational intelligence methods; explains the theoretical background underpinning proposed solutions to common problems; discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms; reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models.<p/><br></br><p><b> From the Back Cover </b></p></br></br><p>This authoritative textbook provides a clear and logical introduction to the field, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. This enhanced second edition to the definitive textbook on <i>Computational Intelligence</i> has been fully revised and expanded with new content on swarm intelligence, deep learning, fuzzy data analysis, and discrete decision graphs.</p> <p><b>Topics and features: </b><br></p><p></p> <p></p><ul><li>Provides electronic supplementary material at an associated website, including module descriptions, lecture slides, exercises with solutions, and software tools</li><li>Contains numerous classroom-tested examples and definitions throughout the text</li><li>Presents useful insights into all that is necessary for the successful application of computational intelligence methods</li><li>Explains the theoretical background underpinning proposed solutions to common problems</li><li>Discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms</li><li>Reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models</li></ul><p></p><p></p> <p>This accessible text is an essential reference for students of artificial intelligence and intelligent systems, and a valuable resource for all researchers and practitioners seeking a self-study primer on computational intelligence.</p><p></p> <p><b>Rudolf Kruse</b> and <b>Sanaz Mostaghim</b> are professors at the Department of Computer Science of the Otto von Guericke University of Magdeburg, Germany. <b>Christian Borgelt</b> is a principal researcher, and <b>Christian Braune</b> is a research assistant at the same institution. <b>Matthias Steinbrecher</b> is with SAP SE, Potsdam, Germany.<br></p><p></p><p/><br></br><p><b> Review Quotes </b></p></br></br><br><p>"It is a great book, very well written, that presents solid content in a very rigorous theoretical and practical way and provides an excellent methodological guide to the area of computational intelligence --one that could be qualified as a 'must' for the library of any student, professor, researcher or professional in that area." (José Luis Verdegay, Mathematical Reviews, May, 2017)</p><br><p/><br></br><p><b> About the Author </b></p></br></br><b>Rudolf Kruse</b> and <b>Sanaz Mostaghim</b> are professors at the Department of Computer Science of the Otto von Guericke University of Magdeburg, Germany. <b>Christian Borgelt</b> is a principal researcher, and <b>Christian Braune</b> is a research assistant at the same institution. <b>Matthias Steinbrecher</b> is with SAP SE, Potsdam, Germany.
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